IoT Automation Trend Rides Next Wave of Machine Learning, Big Data
IoT automation has found new raison d’etre in the COVID-19 era.
July 31, 2020
An array of new methods — along with unexpected new pressures — cast today’s IoT automation efforts in an utterly new light.
Progress today in IoT automation is based on fresh methods employing big data, machine learning, asset intelligence and edge computing architecture. It is also enabled by emerging approaches to service orchestration and workflow, and by ITOps efforts that stress better links between IT and operations.
On one end, advances in IoT automation include robotic process automation (RPA) tools that use sensor data to inform backroom and clerical tasks. On the other end are true robots that maintain the flow of goods on factory floors.
Meanwhile, nothing has focused business leaders on automation like COVID-19. Automation technologies have gained priority in light of 2020’s pandemic, which is spurring use of IoT sensors, robots and software to enable additional remote monitoring. Still, this work was well underway before COVID-19 emerged.
Cybersecurity Drives Advances in IoT Automation
In particular, automated discovery of IoT environments for cybersecurity purposes has been an ongoing driver of IoT automation. That is simply because there is too much machine information to manually track, according to Lerry Wilson, senior director for innovation and digital ecosystems at Splunk. The target is anomalies found in data stream patterns.
“Anomalous behavior starts to trickle into the environment, and there’s too much for humans to do,” Wilson said. And, while much of this still requires a human somewhere “in the loop,” the role of automation continues to grow.
Wilson said Splunk, which focuses on integrating a breadth of machine data, has worked with partners to ensure incoming data can now kick off useful functions in real time. These kinds of efforts are central to emerging information technology/operations technology (IT/OT) integration. This, along with machine learning (ML), promises increased automation of business workflows.
“Today, we and our partners are creating machine learning that will automatically set up a work order – people don’t have to [manually] enter that anymore,” he said, adding that what once took the form of analytical reports now is correlated with historic data for immediate execution.
“We moved past reporting to action,” Wilson said.
Notable use cases Splunk has encountered include systems that collect signals to monitor and optimize factory floor and campus activity as well as to correlate asset information, Wilson indicated.
Hyperautomation Hyped
The move toward more coordinated, highly integrated systems automation is strong enough that Gartner has dubbed it “hyperautomation,” and included it in its “Top 10 Strategic Technology Trends for 2020.”
The research group describes hyperautomation as “the orchestrated use of multiple technologies to catalyze business-driven process change,” and declares “everything that can be automated, will be automated.”
The hyperautomation category includes process and task automation tools, ML, event-driven software and RPA, according to Gartner. Estimates of Coherent Market Insights valued a global market for hyperautomation at $4.2 billion in 2017, and predicted 18.9% CAGR from 2019 through 2027.
Automation — hyper or other — is supported in several products. These include workflow orchestration software from companies ranging from Broadcom and BMC to Radianse and Resolve Systems. The space also holds players like ServiceNow and Splunk.
The ranks include industrial IoT automation systems from GE, Honeywell, Rockwell Automation, Plex, PTC and Siemens, as well as IT infrastructure and ERP application software such as C3.ai, IBM and SAP.
And, that is not to mention domain specialists like Esri, with geospatial data processing; Dassault Systèmes, with 3D Design and engineering software; and many others working to automate aspects of IoT.
Business Process Automation
For Radianse, which integrates intelligent tracking and management software with tagged RFID and non-RFID devices, IoT automation means expanding real-time monitoring of staff tasks and automation of schedules from elder care facilities and hospitals to gyms, fitness centers and even bars.
In hospitals, naturally, asset tracking has gained new importance as respirator demand has vaulted. Cleaning schedules, too, now require new levels of tracking and efficiency. Change here is rapid.
“With the COVID-19 pandemic, you see pivots in approaches. You see interfaces that don’t require touch menus, or that interface to users’ own devices,” according to Randy Ribeck, vice president of strategy for Radianse.
Ribeck said the company works with customers to implement systems that automate scheduling and asset use, and that the influx of data can be challenging. So, paring down incoming data to the essentials is an important mission. “Otherwise, at times, you can be drinking from a fire hose,” he said.
ITOps Automation
Agility has been the mantra of many organizations for years. That’s taken the form of DevOps, ITOps, MLOps and AIOps. All are methods organizations use to automate the repeatable steps developers and administrators take to keep apps running.
As use of IoT devices grows, more automation is being applied. Basically, more organizations are taking on the workflow styles of traditional telcos or cloud providers.
“There is a common problem around the proliferation of IoT [devices]. Organizations are left to manage all of these ‘things,’ to make sure they are working properly,” said Vijay Kurkal, CEO, Resolve Systems, maker of an AIOps platform for enterprise-wide incident response, automation and process orchestration.
The problems grow greater as IoT devices take on more tasks. He cites one of the most ubiquitous of ‘Things.’ That is, the ATM.
“More than ever, banks need to know ATMs are up, running and functioning. That is because each ATM now serves multiple applications. If they fail, you lose business and customers are frustrated,” Kurkal said.
Moreover, a “truck roll” that requires technicians to be dispatched (in a truck) to ATM locations is expensive. All that makes AI and automation an integral part of capable incident resolution planning, he said.
IoT Automation on the Map
Automation takes on a different aspect when IoT data is introduced, according to Susan Foss, product manager for real-time visualization and analytics at Esri, the geographic information system (GIS) giant.
What is different? “It’s the nature of the data being collected,” she said. “Organizations have never had this type of information before or at this granularity of time-space detail.”